Vaibhav Puranik’s Post

The term “AI Hallucination” describes instances where LLMs generate incorrect, misleading, or nonsensical results. However, recent discussions in psychology suggest that “confabulation” is a more accurate term (https://lnkd.in/g4eqCSUy). While hallucination implies a false sensory experience, confabulation refers to the creation of false memories—more akin to what AI does. Understanding these nuances helps us harness AI’s potential while mitigating its shortcomings. At GumGum, we thoughtfully evaluate state-of-the-art technology with rigorous quantitative testing and meticulous manual spot-checking before incorporating it into our existing workflows. This ensures our datasets are curated to remove anomalies and yield top-performing models.

The term “AI Hallucination” describes instances where LLMs generate incorrect, misleading, or nonsensical results. However, recent discussions in psychology suggest that “confabulation” is a more accurate term (https://lnkd.in/gNDC-hUk). While hallucination implies a false sensory experience, confabulation refers to the creation of false memories—more akin to what AI does. Understanding these nuances helps us harness AI’s potential while mitigating its shortcomings. At GumGum, we thoughtfully evaluate state-of-the-art technology with rigorous quantitative testing and meticulous manual spot-checking before incorporating it into our existing workflows. This ensures our datasets are curated to remove anomalies and yield top-performing models.

🚀 Huge News! Now you can see some of the AI automatic note companies to compare side by side. 🔍📊 For full details and answers to your questions, visit the link below. Make sure to check out the bottom of the page for full answers PatientNotes.app Darren Ross Everbility Angela Mariani - Everbility Joshua Spencer 🔗 https://bit.ly/aicompare #AI #TechNews #Innovation #AutomaticNotes #Comparison

Order and Disorder Part II Order and disorder in artificial and human intelligence encompass structured processes, cognitive limitations, and decision-making dynamics. In artificial intelligence, order is linked to structured data processing and rule-based algorithms, while disorder can involve errors, unpredictability, and biased outcomes. Human intelligence demonstrates order through logical reasoning and organized problem-solving, but can also experience disorder through cognitive biases and emotional influences. The intersection of artificial and human intelligence presents opportunities for collaboration and challenges related to integrating diverse cognitive frameworks. Understanding these concepts is crucial for responsible AI deployment and advancing the interaction between artificial and human intelligence.   Part I: https://lnkd.in/d4_6hmuZ

PRICEBEAM WEBINAR https://lnkd.in/eWK4eMCb Pricing Psychology in the Age of AI Modelling New Webinar Designs (1600 x 900 px) Psychology has been around in pricing for decades or even centuries. Charging 9.99 instead of 10, putting in an expensive option to make the other options look more affordable, and many other types of mechanisms. However, in an era where now more and more prices are created using mathematical models, and in some industries AI, how does one take into consideration the age-old truths about how human psychology works when faced with prices in a purchase decision. In the webinar, we will be looking at: Common types of pricing psychology and how they translate into actual prices. Automatic modelling, with and without AI, of optimal price points How to integrate pricing psychology into AI models. This webinar is hosted live by PriceBeam on 29th February 2024 at 10h00 EST, 15h00 GMT, 16h00 CET. Sign up on the right to get your personal invitation.

Imagine a system that can predict and understand human behavior like a person. That’s Centaur, an advanced AI model built on Llama 3.1. Centaur was trained with data from over 60,000 participants and 160 psychology experiments, giving it insight into decision-making, memory, and learning. It uses a technique called QLoRA to specialize without changing its core design. In tests, Centaur outperformed other AI and psychology models, accurately predicting behavior in new situations. Its internal processes also align with human brain activity, making it a groundbreaking tool for understanding how we think. Read more here>https://lnkd.in/dEF3J7G5 

💲AI and Pricing Psychology can help you sell more. Join us this Thursday for our #webinar to see how blending psychology with AI can change your pricing and selling strategies. Learn how changing prices can influence what people think and decide, leading to higher earnings and a stronger position against competitors. Register here 👉🏽 https://priceb.co/3uNxz0D #AI #pricingpsychology #pricingstrategy #revenuegrowth

Innovative AI Self-Connection A recent study shows that engaging with an AI-generated future self can lower anxiety and negative emotions while enhancing one's sense of future self-continuity. This novel approach fosters a stronger connection to future aspirations, offering a unique way to boost emotional resilience. Read the study: https://lnkd.in/eFgJW7fU

Have you ever seen a face in the clouds or in your morning toast? This fascinating phenomenon is known as pareidolia—our brain's tendency to perceive familiar patterns in random stimuli. A recent article dives deep into this topic, revealing that both humans and AI systems share this trait, albeit in different ways. Researchers at MIT discovered that while humans instinctively recognize faces even in inanimate objects, AI does not naturally do so. However, when trained on facial data, AI becomes adept at spotting these illusory faces. They identified the "Goldilocks Zone of Pareidolia," an optimal level of visual complexity for both humans and machines where these perceptions are most likely to occur. The implications of this research are significant. It can enhance face detection systems, improve human-computer interaction, and even inform product design to make items seem more relatable. As we explore the nature of perception—both human and algorithmic—we're left to wonder: is seeing faces everywhere a helpful survival trait or a quirk of our minds? What do you think? Is pareidolia an endearing quirk, or does it highlight potential limitations in our perception? Share your thoughts or check out the full article here: https://lnkd.in/enRtmQw9.

Imagine you have a super-smart friend who knows almost everything instantly and can understand a lot of different things at once. This friend is like a big computer brain called a Large Language Model (LLM). Here's the main idea: 1. Human Thinking: We humans learn and think by slowly gathering bits of information over time, like putting together pieces of a puzzle. We do this through reading, learning, and experiencing things step-by-step. 2. AI Thinking: The LLM, on the other hand, can instantly understand and connect all the information it has learned because it processes everything at once, not step-by-step. This is what the article means by "thinking at a distance" – it’s as if this computer brain can think about and connect things that are far apart really quickly. 3. Working Together: When humans use these LLMs, it's like teaming up with this super-smart friend. This can help us solve problems faster and learn new things more quickly. But, we also need to make sure we trust and understand how this friend thinks and makes decisions, to avoid misunderstandings. 4. Challenges: As we start working more with these AI brains, we have to figure out how to blend our slower, step-by-step thinking with the AI's fast and all-at-once thinking. This means dealing with issues like trust and making sure the AI's decisions fit well with real-world situations. Why It Matters: - Faster Learning: Using AI can help us overcome our natural limits on how fast and how much we can learn. - New Questions: This relationship between humans and AI makes us think about what it really means to be smart and how we can best use our new AI tools. In short, "thinking at a distance" is about using AI to help us think and learn in ways we couldn't do alone, but we need to be careful and thoughtful about how we do this.